Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert interaction to generate GIS-compatible grids of climate variables. This study applied PRISM to generate maps of mean monthly and annual precipitation and minimum and maximum temperature for the Caribbean islands of Puerto Rico, Vieques and Culebra over the 1963-1995 averaging period. PRISM was run under alternative parameterizations that simulated simpler interpolation methods as well as the full PRISM model. For temperature, the standard PRISM parameterization was compared to a hypsometric method, in which the temperature/elevation slope was assumed to be -6.5°C/km (HYPS). For precipitation, the standard PRISM parameterization was compared to an inverse-distance weighting interpolation (IDW). Spatial temperature patterns were linked closely to elevation, topographic position, and coastal proximity. Both PRISM and HYPS performed well for July maximum temperature, but HYPS performed relatively poorly for January minimum temperature, due primarily to lack of a spatially varying temperature/elevation slope, vertical atmospheric layer definition, and coastal proximity guidance. Mean monthly precipitation varied significantly throughout the year, reflecting seasonally differing moisture trajectories. Spatial precipitation patterns were associated most strongly with elevation, upslope exposure to predominant moisture-bearing winds, and proximity to the ocean. IDW performed poorly compared to PRISM, due largely to the lack of elevation and moisture availability information. Overall, the full PRISM approach resulted in greatly improved performance over simpler methods for precipitation and January minimum temperature, but only a small improvement for July maximum temperature. Comparisons of PRISM mean annual temperature and precipitation maps to previously-published, hand-drawn maps showed similar overall patterns and magnitudes, but the PRISM maps provided much more spatial detail.

Critical Zone (CZ) research investigates the chemical, physical, and biological processes that modulate the Earth’s surface. Here, we advance 12 hypotheses that must be tested to improve our understanding of the CZ: (1) Solar-to-chemical conversion of energy by plants regulates flows of carbon, water, and nutrients through plant-microbe soil networks, thereby controlling the location and extent of biological weathering. (2) Biological stoichiometry drives changes in mineral stoichiometry and distribution through weathering. (3) On landscapes experiencing little erosion, biology drives weathering during initial succession, whereas weathering drives biology over the long term.(4) In eroding landscapes, weathering-front advance at depth is coupled to surface denudation via biotic processes.(5) Biology shapes the topography of the Critical Zone.(6) The impact of climate forcing on denudation rates in natural systems can be predicted from models incorporating biogeochemical reaction rates and geomorphological transport laws.(7) Rising global temperatures will increase carbon losses from the Critical Zone.(8) Rising atmospheric PCO2 will increase rates and extents of mineral weathering in soils.(9) Riverine solute fluxes will respond to changes in climate primarily due to changes in water fluxes and secondarily through changes in biologically mediated weathering.(10) Land use change will impact Critical Zone processes and exports more than climate change. (11) In many severely altered settings, restoration of hydrological processes is possible in decades or less, whereas restoration of biodiversity and biogeochemical processes requires longer timescales.(12) Biogeochemical properties impart thresholds or tipping points beyond which rapid and irreversible losses of ecosystem health, function, and services can occur.

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert interaction to generate GIS-compatible grids of climate variables. This study applied PRISM to generate maps of mean monthly and annual precipitation and minimum and maximum temperature for the Caribbean islands of Puerto Rico, Vieques and Culebra over the 1963-1995 averaging period. PRISM was run under alternative parameterizations that simulated simpler interpolation methods as well as the full PRISM model. For temperature, the standard PRISM parameterization was compared to a hypsometric method, in which the temperature/elevation slope was assumed to be -6.5°C/km (HYPS). For precipitation, the standard PRISM parameterization was compared to an inverse-distance weighting interpolation (IDW). Spatial temperature patterns were linked closely to elevation, topographic position, and coastal proximity. Both PRISM and HYPS performed well for July maximum temperature, but HYPS performed relatively poorly for January minimum temperature, due primarily to lack of a spatially varying temperature/elevation slope, vertical atmospheric layer definition, and coastal proximity guidance. Mean monthly precipitation varied significantly throughout the year, reflecting seasonally differing moisture trajectories. Spatial precipitation patterns were associated most strongly with elevation, upslope exposure to predominant moisture-bearing winds, and proximity to the ocean. IDW performed poorly compared to PRISM, due largely to the lack of elevation and moisture availability information. Overall, the full PRISM approach resulted in greatly improved performance over simpler methods for precipitation and January minimum temperature, but only a small improvement for July maximum temperature. Comparisons of PRISM mean annual temperature and precipitation maps to previously-published, hand-drawn maps showed similar overall patterns and magnitudes, but the PRISM maps provided much more spatial detail

We used cosmogenic nuclide and geochemical mass balance methods to measure long-term rates of chemical weathering
and total denudation in granitic landscapes in diverse climatic regimes. Our 42 study sites encompass widely varying climatic
and erosional regimes, with mean annual temperatures ranging from 2 to 25 jC, average precipitation ranging from 22 to 420
cmyear 1, and denudation rates ranging from 23 to 755 tkm 2year 1. Long-term chemical weathering rates range from 0 to
173 tkm 2 year 1, in several cases exceeding the highest granitic weathering rates on record from previous work. Chemical
weathering rates are highest at the sites with rapid denudation rates, consistent with strong coupling between rates of chemical
weathering and mineral supply from breakdown of rock. A simple empirical relationship based on temperature, precipitation
and long-term denudation rates explains 89–95% of the variation in long-term weathering rates across our network of sites. Our
analysis shows that, for a given precipitation and temperature, chemical weathering rates increase proportionally with freshmaterial
supply rates. We refer to this as ‘‘supply-limited’’ weathering, in which fresh material is chemically depleted to roughly
the same degree, regardless of its rate of supply from breakdown of rock. The temperature sensitivity of chemical weathering
rates is two to four times smaller than what one would expect from laboratory measurements of activation energies for feldspar
weathering and previous inter-comparisons of catchment mass-balance data from the field. Our results suggest that climate
change feedbacks between temperature and silicate weathering rates may be weaker than previously thought, at least in actively
eroding, unglaciated terrain similar to our study sites. To the extent that chemical weathering rates are supply-limited in
mountainous landscapes, factors that regulate rates of mineral supply from erosion, such as tectonic uplift, may lead to
significant fluctuations in global climate over the long term.

We used a humid tropical elevation gradient to examine the relationships among climate, edaphic conditions, belowground carbon storage, and soil respiration rates. We also compared open and closed canopy sites to increase the range of microclimate conditions sampled along the gradient, and determine the effects of canopy openings on C and P storage, and C dynamics. Total soil C, the light C fraction, and all of the component fractions of the P pool were significantly related to soil moisture, and all but total soil C were also significantly related to temperature. Both labile and recalcitrant soil P fractions were negatively correlated with the light C fraction, while the dilute HCl-extractable P pool, generally thought of as intermediate in availability, was positively correlated with light C, suggesting that P may play an important role in C cycling within these systems. Total fine root biomass was greatest at 1000 m elevation and lowest at 150 m, and was strongly and positively correlated with soil moisture content. Soil respiration rates were significantly and negatively correlated with fine root biomass and the light C fraction. In forested sites, soil respiration rates were strongly and negatively correlated with total belowground C pools (soils 1 roots 1 forest floor). Belowground C pools did not follow the expected increasing trend with decreases in temperature along the gradient. Our results indicated that in humid tropical forests, the relationships among soil C and nutrient pools, soil respiration rates, and climate are complex. We suggest that frequent and prolonged anaerobic events could be important features of these environments that may explain the observed trends.